Integrating geospatial information in the analysis of network disruptions

Meda, Harshitha; Vogiatzis, Chrysafis; Davis, Lauren B.

doi:10.1016/j.ijdrr.2023.103569

Cited by 2 publications

(1 citation statement)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The airline networks are easily affected by unexpected disruptions, such as natural disasters, technical and human errors and public health emergencies. For example, Meda et al [1] indicated the North American winter storm in late December 2022 caused weather delay and cancellation, mainly due to technical and human factors of Southwest Airlines. Su et al [2] also stated that, in 2019, about 21% of flights in the United States experienced over 15 minutes of arrival delay, while the average flight on-time rate in China was 81.43%.…”

Section: Introductionmentioning

confidence: 99%

Optimizing capacitated hub-and-spoke airline network under disruption

Guo,

Yang

2024

Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023)

View full text Add to dashboard Cite

This paper addresses the capacitated hub-and-spoke airline network design problem under disruption. Specifically, this paper extends the classical hub-and-spoke airline network design problem by considering hub (airport) capacity and various disruption risks. In particular, this paper proposes a backup hub strategy to protect the designed airline network against the disruption risk. This paper formulates a mixed-integer nonlinear programming (MINLP) model for the considered problem for minimizing the sum of the construction cost of the backup hubs and the expected total transportation cost of the new airline network formed by backup hubs after disruption. Through a series of numerical experiments based on a simulated example, this paper verifies the practical value for the capacity constraints of the hub airports to enhance the ex-ante resilience. This paper also conducts sensitivity analysis on inter-hub discount factor and probability of hub disruption to provide managerial implications for airline company.

show abstract

Section: Introductionmentioning

confidence: 99%